presented by: andrew setzer project manager, nysed higher education longitudinal data warehouse...
TRANSCRIPT
Presented by: Andrew Setzer
Project Manager, NYSED Higher Education Longitudinal Data Warehouse
Ellen Moore Administrative Coordinator, Student Data Services
Education & Information Support Services, Eastern Suffolk BOCES
March 15, 2013NYS DATAG
Linking P-12 with the NYS Higher Ed
Data Warehouse
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Linking P-12 with the NYS Higher Ed Data Warehouse
Starting with data from the National Student Clearinghouse, linkages have been made with data in our P-12 data warehouses
for several years. This presentation will examine some innovative reports, controversial findings, and future topics for study. This presentation will also report on the NYSED initiative to build a
data warehouse starting with data from SUNY and CUNY colleges and other post-secondary institutions.
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School Report Card
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Race To The Top for High Schools
High school has a new mission. No longer is it enough just to graduate students, or even prepare them for college. Schools must now show how they increase both college enrollment and the number of students who complete at least a year ofcollege. In other words, high school must now focus on grade 13.
New York TimesOP-ED ContributionsHigh School’s Last TestBy J.B. Schramm and E. Kinney Zalesne
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College Board Begins SAT RedesignDavid Coleman: "We will develop an assessment that mirrors the work that students will do in college so that they will practice the work they need to do to complete college." Among the objectives that will drive the College Board's work, Coleman mentioned increasing the value of the SAT to K-12 teachers, administrators, and counselors by strengthening the alignment of the SAT to college and career readiness; making sure content reflects excellence in classroom instruction; and developing companion tools that use SAT results to improve instruction and curriculum.
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Implementation of the Common Core Learning Standards
The need for this change is readily apparent. In June 2011, SED released(http://www.p12.nysed.gov/irs/pressRelease/20110614/home.html ) for the first time“aspirational performance measures,” or New York graduation rates based on college and career-readiness performance standards: Only 30.9% of the 2006 cohort graduated with a Regents diploma with Advanced Designation, and only 36.7% of the graduates in the cohort scored at least 75 and 80 on their English and math Regents exams, respectively (these Regents exam cut scores are considered to be the minimum necessary for college-readiness). These high school results are consistent with New York’s elementary and middle school scores on NAEP: for the 2011 school year, only 30% and 35% of New York’s Grade 8 students scored proficient on the NAEP in math and reading, respectively. These sobering high school outcomes make it even more important that our new Grades 3-8 ELA and math Common Core assessments provideeducators and parents with early indicators of the trajectory to college- and career readiness long before our students enter high school.
Ken Slentz, Deputy Commissioner, Office of P-12 Education, March 2013
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The Critical Factor
Find out which educational strategies actually result in student success after high school.
In 2008, Student Data Services started offering school districts the opportunity to obtain postsecondary data that will be stored in the data warehouse. Working with the data warehouse, school leaders have the ability to analyze postsecondary data reports and to design customized reports for the same purpose.
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A New Standard for Proficiency: College Readiness
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In the past, we defined proficiency in relation to grade level standards. Such a definition did not provide children, families, and the schools that serve them with an indication of whether students were on a trajectory for college success.
Now, we will redefine proficiency for students in New York State to mean that a student is on track to succeed in college without the need for remediation.
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The New Bar…for Kids!
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ELA
MATH
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The New Bar
• Less Than 80 on Math Regents and Less Than 75 on ELA Regents Results in Greater Likelihood for Remedial College Coursework
• “Proficient” in Grade 8 Math Prior to 2010: Less than 33% Chance at scoring 80 on Integrated Algebra
• “Proficient” in Grade 8 ELA Prior to 2010: 50% Chance at Scoring 75 on ELA Regents
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Reports based on StudenTracker from NSC
• Which of your students went to college?• Where did they enroll?• Did they graduate?
StudentTracker for High Schools answers these questions and more by matching a district’srecords against the Clearinghouse’s database.
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Let’s look at some
Cognos Reports
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Drill-Through Detail
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With Suffolk County averages on the last page
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Plans and Outcomes Report
District Name
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Plans and Outcomes Report
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Plans and Outcomes Report
District Name
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College Tracking Detail Report
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Cost of Remedial Coursework
New York’s graduation rates have increased in recent years. Of the public school students who entered ninth grade in 2007, 74% percent graduated four years later. However, the good news about the rise in the graduation rate does not tell a full story. Despite New York State having some of the most successful individual districts and individual schools in the country, too many of our students do not graduate, and too many of our high school graduates find themselves taking remedial courses when they enter college. These students pay college tuition for learning that should have happened in high school, and students who take remedial courses in college are less likely to finish their studies. Students who do not complete post-secondary education often have to accept jobs that do not provide a family-supporting wage and do not offer potential for meaningful advancement. This outcome hurts us all – our children, our families, New York, and the nation. When our educational system fails to prepare so many of our children for success in college and their careers, we are all accountable.
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A Missing Link
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Measures of Success
Long-term results of our efforts Career and College Readiness Performance Measures of targeted
programs Counselor reflection on case-load
outcomes
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Intervention and Early Warning• Construct validity - Several measures, taken together, more adequately
sample the things students should know and be able to do in the achievement domain being measured. Using more than one measure also helps us recognize performance variations caused by format, timing, and other logistical aspects of testing.
• Decision validity - For any particular decision, there are usually several relevant types of information, each of which could have one or more measures.
For example, to decide whether a school is doing a good job, several different achievement measures need to be considered, (reading, mathematics, and so on); as well as information about resources (personnel, finance, policies); processes (curriculum, instruction, school climate); and other school outcomes (safety, graduation rate, student and parent satisfaction).
GRAZMOR ASSOCIATES,INC 2013 42
Additional Measures of Success
–Enrollment in second year–Degree completion
• 4 year graduation• 5 -6 year graduation
–Graduate enrollment/degrees–Remedial course enrollment–College grades
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“The linking of the P-12 and higher education data
systems will allow for richer longitudinal analyses and the
identification of additional opportunities to improve
educational programs and prepare students for college
and careers.”
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Questions beyond P-12 and NSC
How many of your high school graduates need to take remedial courses in college?
How do your high school graduates perform in their college courses?
Does success on high school exams translate to success in college?
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Questions beyond P-16
How do teacher prep program course grades equate with student performance on state tests?
What college courses/programs lead to successful employment?
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Higher EducationLongitudinal Data System
(HE LDS) Project Funding, Goals, Challenges, and Buy-in
• RTTT, 2 IES grants, Capital Funds from NYS Legislature
• FERPA and related privacy concerns• Technology and resource challenges• Importance of research and data
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HE LDS Goals• Create and Implement a 13 - 20 System with Interactive Links to
the expanded P-12 system– Expand the Architecture and Functionality of the P-12 Module and
Implement a Higher Education LDS – Plan and Implement Standardized Higher Education Course Information– Identify "gatekeeper" and teacher preparation courses with SUNY/CUNY– Standardize course codes with SUNY/CUNY– Implement collection in SUNY/CUNY– Implement collection in private universities– Plan the Linkages to Health/Human Services/Workforce and other Data– Expand comprehensive student identifier system– Implement reporting linkages across four State agencies
• Create and Implement an Instructional Support System– Design the Reports for a P-16 Comprehensive Instructional Support
System
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Original Goalsof the NYS HE LDS Project
• For the 2011-12 school year, SUNY and CUNY will provide end-of-term student-level data to the Department’s P-20 data system. This information will include the student’s institution of higher education enrollment, full/part-time enrollment status, academic program of study, credit hours earned, participation in remedial coursework, and completed degrees. In addition, SUNY and CUNY will begin to integrate the statewide P-12 unique student identifier into their campus systems and processes.
• At the conclusion of the 2011-12 school year, these higher education data will allow the Department to evaluate career- and college-ready metrics (e.g., students who graduate from high school with a 75 or greater on the English language arts Regents and a 80 or greater on a math Regents) as a predictor of whether a student is required to enroll in a college remediation program across both CUNY and SUNY campuses.
• Beginning with the 2012-13 school year, NYSED will begin to collect student enrollment and performance in key courses from SUNY and CUNY, including teacher preparation coursework, “gatekeeper” courses (e.g., freshman English and math), and enrollment in courses designed to support the needs of students with disabilities and English language learners.
• At the conclusion of the 2012-13 school year, NYSED will also be able to evaluate career- and college-ready standards as a predictor of grades earned in key college courses (e.g., freshman English) across both CUNY and SUNY campuses.
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The Progress to date
• SUNY, CUNY, Level 2, eScholar, NYSED (HE and IRS), Regents Research Fellow and a Project Manager– ‘phases’ and timelines– Start with Fall 2011 data
• Possible future project improvements• Your feedback and suggestions
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NYSSIS Matching
• Received files for Fall 2011 from CUNY (236,899 records) and SUNY (482,984 records)
• There is no ‘hold queue’ for manual review• Agreement to also submit Summer 2011• Agreement to also submit 2010-2011
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NYSSIS Matching• If there is a P-12 candidate with a match percentage
of 90% or greater for a Higher Ed. record, it is automatically matched.
• Normally records with candidates that have a match percentage less than 90% and greater than 35% would end up in the hold queue.
• NYSSIS has the business rule coded that will not allow Higher Ed. records to go to the hold queue for a user to resolve. Instead NYSSIS will "try again" to match a P12 record that is reasonable or NYSSIS will assign a new NYSSIS ID.
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NYSSIS Matching – some stats
• SUNY file: NYSSIS found a match for about two-thirds of initially submitted records
• ‘Older’ students, non-NYS residents, and non-public students (~14.3%) may not get NYSSIS ID’s
• Test files (2 campuses)– Focus on students with NYS HS CEEB codes born in 1990 or
later– 93.62% and 97.90% respectively; 95.25% overall
• All SUNY = 95.92%
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NYSSIS Matching – some stats• Local HS S to Suffolk CCC – 245/247 = 99.19%• Local HS N to Nassau CCC – 383/384 = 99.74%• Local HS O to Onondaga CCC – 239/240 = 99.58%• Local HS D to Dutchess CCC – 336/338 = 99.41%• Local HS B to Broome CCC – 334/337 = 99.11%• Local HS S to All SUNY - 509/513 = 99.22%• Summary of above*: 1801/1812 = 99.39%
• Future issues: – Is 99.39% good enough?– Correcting mistakes?– Using a manual hold queue?– Other ?
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Target P-16 Submission CalendarAll campuses will be required to submit data two times
per year:
April 1st
For data from the Summer and Fall Terms(All terms ending between July 1 and December 31)
andAnnual Data for the preceding year
August 1st
For data from the Winter and Spring Terms(All terms ending between January 1 and June 30)
*NYSSIS ID File Submissions can be submitted at any time, but please avoid submitting files from September 1 to November 15. Thank you.
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Phase 1 (4 templates)
• PS Student Institution– Name, DOB, ethnicity/race, gender, citizenship, etc.
• PS Student Enrollment– Info about student enrollment, majors, minors, degree
seeking, dual enrollment, graduation, etc.
• Campus Student Fact Template– Info about remedial enrollment, hours, completion, etc.
• Campus Student Program Fact Template– Student support services participation
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Phase 2 (6 templates)• PS Student Credit GPA
– Term GPA and credits and cumulative GPA and credits• PS Student Transfer Fact
– Info on transfer students• Student Educational Background
– HS graduation and GPA info• Student Qualification
– Exams and scores for entrance, placement, etc.• PS Course Campus
– Course codes, titles, descriptions, subject, credit, etc.• PS Student Class Detail
– Student class grades, credits, outcomes, etc.
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Phase 2
• Student Educational Background• Student Qualification• PS Student Transfer Fact• PS Student Credit GPA• PS Course Campus• PS Student Class Detail
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Phase 2
• Student Educational Background• Student Qualification• PS Student Transfer Fact• PS Student Credit GPA• PS Course Campus• PS Student Class Detail
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Phase 3 (planned summer 2013)
• Student Award– Degrees, diplomas, certificates, etc.
• Student Campus Expense– Tuition, room & board, books, etc.
• Student Campus Financial Aid– Federal grants, state loans, etc.
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Phase 4 (planning not finalized)
PS Student Admissions ?And more?
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Upcoming Activities• Course and Class templates – April target• Submit Phase 1 and 2 data for all 2011-2012 terms• Develop schedule for 2010-2011 and 2012-2013 data• Reporting site
– documents– counts and verification of data loads– Cross template reports– extracts for researchers at SED and RRF– reports linking HE and P-12 data– analysis reports– Data for P-12 districts?
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Future Project Improvements?
• Class and Course data refinements• Collect other/different/new templates• Product enhancements• NYSSIS improvements• Adding non-public colleges?• NYSSIS ID in TEACH System?• Continue to review data submission schedule• What else might we want to do?
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Andy’s Analogy:
Building a data warehouse is like saving for retirement. It is a long term project.
It does require a great deal of time, patience, steady investment, and adjustment.
There will be a great payoff.
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